{"title":"21. Groundwater Pollution Control","authors":"D. Watkins, D. McKinney, D. Morton","doi":"10.1137/1.9780898718799.CH21","DOIUrl":"https://doi.org/10.1137/1.9780898718799.CH21","url":null,"abstract":"Groundwater is an important source of potable water because it is abundant and readily available in many locations and often requires little or no treatment. In 1995, groundwater accounted for approximately 20% of potable water use in the U.S., and approximately 50% of the U.S. population relied on groundwater for their source of drinking water. In most European countries, groundwater accounts for 10-50% of potable water use [1]. Unfortunately, various human activities have resulted in the overuse or degradation of many groundwater resource systems. Overpumping (or groundwater mining, the extraction of groundwater at rates higher than natural recharge rates) has led to increased pumping costs, land subsidence, saltwater intrusion into freshwater aquifers, and limited ability to achieve sustainable social and economic systems. Large-scale groundwater pollution has resulted from the use of agricultural chemicals, and localized pollution has resulted from industrial discharges, improper hazardous waste disposal, landfill seepage, and leaky underground storage tanks. Since the management of a groundwater system can be a complex task, a systems analysis framework is frequently used to address groundwater pollution problems. In particular, numerical groundwater simulation models are now commonly used by engineers and scientists to address a wide range of problems involving water supply management, pollution control, and ecosystem protection or restoration. These models are capable of simulating groundwater flow and contaminant transport and predicting the impact of human stresses—pumping or recharge modifications—on the groundwater system. Inputs to these","PeriodicalId":403781,"journal":{"name":"Applications of Stochastic Programming","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123610907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"3. The IBM Stochastic Programming System","authors":"A. King, S. E. Wright, G. Parija, R. Entriken","doi":"10.1137/1.9780898718799.ch3","DOIUrl":"https://doi.org/10.1137/1.9780898718799.ch3","url":null,"abstract":"IBM’s stochastic programming product, Optimization Solutions and Library Stochastic Extensions (OSLSE), was developed at IBM Research’s Thomas J. Watson Research Center in Yorktown Heights, New York, during 1990–2002. It is a library of subroutines that may be linked with user-written C/C++ programs to model and solve multiperiod stochastic linear programs with recourse. Features include quadratic objectives, integer variables, empirical tree generation, and a flexible nested decomposition solver. A parallel version of the nested decomposition solver is also available. The current version (version 3) has been extensively revised from its initial 1998 release. It now uses the OSL version 3 C/C++ infrastructure for problem data management and solver utilities. OSLSE may be freely downloaded with a 60-day try-and-buy license from the OSL website, http://www-3.ibm.com/software/data/bi/osl/index.html. Free academic licenses are available for students and academic researchers.","PeriodicalId":403781,"journal":{"name":"Applications of Stochastic Programming","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121691203","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}